[jira] [Resolved] (SPARK-16206) Defining our own folds using CrossValidator

["Sean Owen (JIRA)" <ji...@apache.org>]

     [ https://issues.apache.org/jira/browse/SPARK-16206?page=com.atlassian.jira.plugin.system.issuetabpanels:all-tabpanel ]

Sean Owen resolved SPARK-16206.
-------------------------------
    Resolution: Not A Problem

If this is more of a discussion, ask at user@. You can implement whatever you want to produce folds though, so not clear what this is about.

> Defining our own folds using CrossValidator
> -------------------------------------------
>
>                 Key: SPARK-16206
>                 URL: https://issues.apache.org/jira/browse/SPARK-16206
>             Project: Spark
>          Issue Type: Wish
>          Components: ML
>    Affects Versions: 1.6.2
>            Reporter: Danilo Bustos
>            Priority: Trivial
>
> I have been using cross validation process in order to train a Naive Bayes Model and I realize that it uses kFold method to get the random sampling data in order to create the folds. This method return an Array[(RDD[T], RDD[T])] of tuples, which I think are the set of different combination of the folds for training and testing.
> My question is whether there is any specific reason because the API does not allow you to define your own array of folds. I think would be a good idea if this capability is supported, it would help a lot. 
> Please refer to: http://stackoverflow.com/questions/37868984/why-we-can-not-define-our-own-folds-when-we-are-using-crossvalidator



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